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Context. With its origin coming from several sources (Big Bang, stars, cosmic rays) and given its strong depletion during its stellar lifetime, the lithium element is of great interest as its chemical evolution in the Milky Way is not well understood at present. To help constrain stellar and galactic chemical evolution models, numerous and precise lithium abundances are necessary for a large range of evolutionary stages, metallicities, and Galactic volume. Aims. In the age of stellar parametrization on industrial scales, spectroscopic surveys such as APOGEE, GALAH, RAVE, and LAMOST have used data-driven methods to rapidly and precisely infer stellar labels (atmospheric parameters and abundances). To prepare the ground for future spectroscopic surveys such as 4MOST and WEAVE, we aim to apply machine learning techniques to lithium measurements and analyses. Methods. We trained a convolution neural network (CNN), coupling Gaia-ESO Survey iDR6 stellar labels (Teff, log(g), [Fe/H], and A(Li)) and GIRAFFE HR15N spectra, to infer the atmospheric parameters and lithium abundances for ∼40 000 stars. The CNN architecture and accompanying notebooks are available online via GitHub. Results. We show that the CNN properly learns the physics of the stellar labels, from relevant spectral features through a broad range of evolutionary stages and stellar parameters. The lithium feature at 6707.8 Å is successfully singled out by our CNN, among the thousands of lines in the GIRAFFE HR15N setup. Rare objects such as lithium-rich giants are found in our sample. This level of performance is achieved thanks to a meticulously built, high-quality, and homogeneous training sample. Conclusions. The CNN approach is very well adapted for the next generations of spectroscopic surveys aimed at studying (among other elements) lithium, such as the 4MIDABLE-LR/HR (4MOST Milky Way disk and bulge low- and high-resolution) surveys. In this context, the caveats of machine-learning applications should be appropriately investigated, along with the realistic label uncertainties and upper limits for abundances. [ABSTRACT FROM AUTHOR]

Context. It is generally agreed upon that stars form in open clusters (OCs) and stellar associations, but little is known about structures in the Galactic OC population; whether OCs and stellar associations are born isolated or if they prefer to form in groups, for example. Answering this question provides new insight into star and cluster formation, along with a better understanding of Galactic structures. Aims. In the past decade, studies of OC groupings have either been based solely on spatial criteria or have also included tangential velocities for identifications. In contrast to previous approaches, we assumed that real OC groupings occupy a well defined area in the sky and show similar velocity vectors. For the first time, we have used 6D phase-space information, including radial velocities from the RAdial Velocity Experiment (RAVE) and other catalogues, for the detection of OC groupings. We also checked the age spread of potential candidates to distinguish between genuine groupings and chance alignments. Methods. We explored the Catalogue of Open Cluster Data (COCD) and determined 6D phase-space information for 432 out of 650 listed OCs and compact associations. The group identification was performed using an adapted version of the Friends-of-Friends algorithm, as used in cosmology, with linking lengths of 100 pc and 10-20 km s-1. For the verification of the identified structures, we applied Monte Carlo simulations with randomised samples. Results. For the linking lengths 100 pc and 10 km s-1, we detected 19 groupings, including 14 pairs, 4 groups with 3-5 members, and 1 complex with 15 members. The Monte Carlo simulations revealed that, in particular, the complex is most likely genuine, whereas pairs are more likely chance alignments. A closer look at the age spread of the complex and the comparison between spatial distributions of young and old cluster populations suggested that OC groupings likely originated from a common molecular cloud. [ABSTRACT FROM AUTHOR]

The past decade and a half has seen the design and execution of several ground-based spectroscopic surveys, both Galactic and Extragalactic. Additionally, new surveys are being designed that extend the boundaries of current surveys. In this context, many important considerations must be done when designing a spectrograph for the future. Among these is the determination of the optimum wavelength coverage. In this work, we present a new code for determining the wavelength ranges that provide the optimal amount of information to achieve the required science goals for a given survey. In its first mode, it utilizes a user-defined list of spectral features to compute a figure-of-merit for different spectral configurations. The second mode utilizes a set of flux-calibrated spectra, determining the spectral regions that show the largest differences among the spectra. Our algorithm is easily adaptable for any set of science requirements and any spectrograph design. We apply the algorithm to several examples, including 4MOST, showing the method yields important design constraints to the wavelength regions. [ABSTRACT FROM AUTHOR]

4MOST is a wide-field, high-multiplex spectroscopic survey facility under development for the VISTA telescope of the European Southern Observatory (ESO). Its main science drivers are in the areas of galactic archeology, high-energy physics, galaxy evolution and cosmology. 4MOST will in particular provide the spectroscopic complements to the large area surveys coming from space missions like Gaia, eROSITA, Euclid, and PLATO. 4MOST will have an unique operations concept in which 5-years public surveys from both the consortium and the ESO community will be combined and observed in parallel during each exposure, resulting in more than 25 million spectra of targets spread over a large fraction of the southern sky. As a dedicated spectroscopic survey facility with a large field-of-view, a high multiplex that can be reconfigured quickly, and with a broad wavelength coverage, 4MOST is particularly well suited to complement the upcoming asteroseismology space missions like TESS and PLATO. Here we show that, by dedicating the observing time during twilight and poor observing conditions to bright stars, 4MOST will obtain resolution R > 18000 spectra of nearly all stars brighter than 12th magnitude at Dec <30° every 2 years. 4MOST is also expected to spectroscopically complement any fainter asteroseismology target tobe observed with PLATO. These observations will provide a chemical characterization of nearly all stars tobe observed with the TESS and PLATO missions and place any planets found in a full chemo-dynamical context of the star formation history of the Galaxy, yield very accurate ages and masses for all stars that can be characterized with asteroseismology, and allow removal of contaminants from target samples (e.g., spectroscopic binaries). [ABSTRACT FROM AUTHOR]

From stellar spectra, a variety of physical properties of stars can be derived. In particular, the chemical composition of stellar atmospheres can be inferred from absorption line analyses. These provide key information on large scales, such as the formation of our Galaxy, down to the small-scale nucleosynthesis processes that take place in stars and supernovae. By extending the observed wavelength range toward bluer wavelengths, we optimize such studies to also include critical absorption lines in metal-poor stars, and allow for studies of heavy elements ( Z ≥ 38) whose formation processes remain poorly constrained. In this context, spectrographs optimized for observing blue wavelength ranges are essential, since many absorption lines at redder wavelengths are too weak to be detected in metal-poor stars. This means that some elements cannot be studied in the visual-redder regions, and important scientific tracers and science cases are lost. The present era of large public surveys will target millions of stars. It is therefore important that the next generation of spectrographs are designed such that they cover a wide wavelength range and can observe a large number of stars simultaneously. Only then, we can gain the full information from stellar spectra, from both metal-poor to metal-rich ones, that will allow us to understand the aforementioned formation scenarios in greater detail. Here we describe the requirements driving the design of the forthcoming survey instrument 4MOST, a multi-object spectrograph commissioned for the ESO VISTA 4 m-telescope. While 4MOST is also intended for studies of active galactic nuclei, baryonic acoustic oscillations, weak lensing, cosmological constants, supernovae and other transients, we focus here on high-density, wide-area survey of stars and the science that can be achieved with high-resolution stellar spectroscopy. Scientific and technical requirements that governed the design are described along with a thorough line blending analysis. For the high-resolution spectrograph, we find that a sampling of ≥2.5 (pixels per resolving element), spectral resolution of 18000 or higher, and a wavelength range covering 393-436 nm, is the most well-balanced solution for the instrument. A spectrograph with these characteristics will enable accurate abundance analysis (±0.1 dex) in the blue and allow us to confront the outlined scientific questions. (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

Context. Galactic open clusters (OCs) mainly belong to the young stellar population in the Milky Way disk, but are there groups and complexes of OCs that possibly define an additional level in hierarchical star formation? Current compilations are too incomplete to address this question, especially regarding radial velocities (RVs) and metallicities ([M/H]). Aims. Here we provide and discuss newly obtained RV and [M/H] data, which will enable us to reinvestigate potential groupings of open clusters and associations. Methods. We extracted additional RVs and [M/H] from the RAdial Velocity Experiment (RAVE) via a cross-match with the Catalogue of Stars in Open Cluster Areas (CSOCA). For the identified OCs in RAVE we derived RV and [M/H] from a cleaned working sample and compared the results with previous findings. Results. Although our RAVE sample does not show the same accuracy as the entire survey, we were able to derive reliable RV for 110 Galactic open clusters. For 37 OCs we publish RV for the first time. Moreover, we determined [M/H] for 81 open clusters, extending the number of OCs with [M/H] by 69. [ABSTRACT FROM AUTHOR]